April 2024 arXiv papers — page 38

Michael R. Geller

Nonlinear mean field dynamics enables quantum information processing operations that are impossible in linear one-particle quantum mechanics. In this approach, a register of bosonic qubits (such as neutral atoms or polaritons) is initialized into a symmetric product state through condensation, then subsequently controlled by varying the qubit-qubit interacti

Zhe Zhang, Ryumei Nakada, Linjun Zhang

Differentially private federated learning is crucial for maintaining privacy in distributed environments. This paper investigates the challenges of high-dimensional estimation and inference under the constraints of differential privacy. First, we study scenarios involving an untrusted central server, demonstrating the inherent difficulties of accurate estima

Guoqiang Wu, Jia-Yong Wu

In this paper, we prove some Willmore-type inequalities for closed hypersurfaces in weighted manifolds with nonnegative Bakry-\'Emery Ricci curvature. In particular, we give a sharp Willmore type inequality in steady gradient Ricci solitons. We also prove a sharp Willmore-like inequality in shrinking gradient Ricci solitons. Moreover, we characterize the equ

Alexander Varchenko, Vadim Vologodsky

The KZ equations are differential equations satisfied by the correlation functions (on the Riemann sphere) of two-dimensional conformal field theories associated with an affine Lie algebra at a fixed level. They form a system of complex partial differential equations with regular singular points satisfied by the $n$-point functions of affine primary fields.

Katharina Laubscher, Jay D. Sau, Sankar Das Sarma

It was recently suggested that proximitized gate-defined Ge hole nanowires could serve as an alternative materials platform for the realization of topological Majorana zero modes (MZMs). Here, we theoretically study the expected experimental signatures of Ge-based MZMs in tunneling conductance measurements, taking into account that unintentional random disor

Chang-Yu Guo, Chang-Lin Xiang, Ming-Lun Liu

In a recent work, Gastel and Neff introduced an interesting system from a geometrically nonlinear flat cosserat micropolar model and established interior regularity in the critical dimension. Inspired by their work on this flat Cosserat model, in this article, we establish both interior regularity and sharp $L^p$ regularity for their system in supercritical

Kang Liu

Taking inspiration from Set Theory, we introduce SetCSE, an innovative information retrieval framework. SetCSE employs sets to represent complex semantics and incorporates well-defined operations for structured information querying under the provided context. Within this framework, we introduce an inter-set contrastive learning objective to enhance comprehen

Fatemeh Dehrouyeh, Li Yang, Firouz Badrkhani Ajaei, Abdallah Shami

As technology advances, the use of Machine Learning (ML) in cybersecurity is becoming increasingly crucial to tackle the growing complexity of cyber threats. While traditional ML models can enhance cybersecurity, their high energy and resource demands limit their applications, leading to the emergence of Tiny Machine Learning (TinyML) as a more suitable solu

Jiachen Liu, Jae-Won Chung, Zhiyu Wu, Fan Lai

Large language models (LLMs) are now at the core of conversational AI services such as real-time translation and chatbots, which provide live user interaction by incrementally streaming text to the user. However, existing LLM serving systems fail to provide good user experience because their optimization metrics are not always aligned with user experience. I

Chuiliu Kong, Ying Wang

This paper considers an adaptive tracking control problem for stochastic regression systems with multi-threshold quantized observations. Different from the existing studies for periodic reference signals, the reference signal in this paper is non-periodic. Its main difficulty is how to ensure that the designed controller satisfies the uniformly bounded and e

Md Kamran Chowdhury Shisher, Yin Sun, I-Hong Hou

In this paper, we analyze the impact of data freshness on remote inference systems, where a pre-trained neural network blue infers a time-varying target (e.g., the locations of vehicles and pedestrians) based on features (e.g., video frames) observed at a sensing node (e.g., a camera). One might expect that the performance of a remote inference system degrad

Sichen Tao, Ruihan Zhao, Kaiyu Wang, Shangce Gao

Complex single-objective bounded problems are often difficult to solve. In evolutionary computation methods, since the proposal of differential evolution algorithm in 1997, it has been widely studied and developed due to its simplicity and efficiency. These developments include various adaptive strategies, operator improvements, and the introduction of other

Bin Chen, Shao-Ming Fei

We investigate the trade-off relations between imaginarity and mixedness in arbitrary $d$-dimensional quantum systems. For given mixedness, a quantum state with maximum imaginarity is defined to be a "maximally imaginary mixed state" (MIMS). By using the $l_{1}$ norm of imaginarity and the normalized linear entropy, we conclusively identify the MIMSs for bot

Soumen Bag, Jesse Kapeghian, Onur Erten, Antia S. Botana

Transition metal dihalides (MX$_2$, M= transition metal, X= halide) have attracted much attention recently due to their intriguing low-dimensional magnetic properties. Particular focus has been placed in this family in the context of multiferroicity -- a common occurrence in MX$_2$ compounds that adopt non-collinear magnetic structures. One example of helima

Olawale Salaudeen, Sanmi Koyejo

Given a causal graph representing the data-generating process shared across different domains/distributions, enforcing sufficient graph-implied conditional independencies can identify domain-general (non-spurious) feature representations. For the standard input-output predictive setting, we categorize the set of graphs considered in the literature into two d

Hennadii Yerzhakov, Tien-Tien Yeh, Alexander Balatsky

We investigate the effects of a Laguerre-Gaussian (LG) beam on the superconducting state. We show that the vortex angular momentum of a LG beam affects the superconducting state and induces currents. The induction of the current by light is illustrated on a Josephson loop and SQUID devices. In particular, we establish that coupling a dc SQUID to the AC magne

Zhiyong Feng, Zhiqing Wei

In this chapter, we investigate the spectrum measurement results in Asia-Pacific region. Then the spectrum sharing policy in the Asia-Pacific region is reviewed in details, where the national projects and strategies on spectrum refarming and spectrum sharing in China, Japan, Singapore, India, Korea and Australia are investigated. Then we introduce the spectr

Ryusuke Sugimoto, Christopher Batty, Toshiya Hachisuka

We present a velocity-based Monte Carlo fluid solver that overcomes the limitations of its existing vorticity-based counterpart. Because the velocity-based formulation is more commonly used in graphics, our Monte Carlo solver can be readily extended with various techniques from the fluid simulation literature. We derive our method by solving the Navier-Stoke

Fengqiao Luo

We develop a novel gradient-based algorithm for optimizing nonsmooth nonconvex functions where nonsmoothness arises from explicit nonsmooth operators in the objective's analytical form. Our key innovation involves encoding active smooth branches of these operators, enabling both branch function extraction at arbitrary points and transition detection through

Nicole F. Bell, Giorgio Busoni, Sandra Robles, Michael Virgato

We present an improved treatment for the scattering of heavy dark matter from the ion constituents of a white dwarf. In the heavy dark matter regime, multiple collisions are required for the dark matter to become gravitationally captured. Our treatment incorporates all relevant physical effects including the dark matter trajectories, nuclear form factors, an

Yang Liu, Pengyu Liu, Yingyi Wen, Zihan Liang

True random numbers are essential in various research and engineering problems. Their generation depends upon a robust physical entropy noise. Here, we present true random number generation by harnessing the conductance noise probed in structurally metastable 1T' molybdenum ditelluride (MoTe2). The noise, well-fitting a Poisson process, is proved a robust ph

Luis A. Manzaneda, César O. Navarrete, Emilio Tejeda

A binary stellar system that ventures too close to a supermassive black hole can become tidally separated. In this article, we investigate the role of relativistic effects in these encounters through 3-body simulations. We use the Hybrid Relativistic-Newtonian Approximation (HRNA), which combines the exact relativistic acceleration from a Schwarzschild black

Kazuya Echigo, Abhishek Cauligi, Behçet Açıkmeşe

In this paper, we consider the problem of minimum-time optimal control for a dynamical system with initial state uncertainties and propose a sequential convex programming (SCP) solution framework. We seek to minimize the expected terminal (mission) time, which is an essential capability for planetary exploration missions where ground rovers have to carry out

Akshatha Mohan, Joshua Peeples

Pooling layers (e.g., max and average) may overlook important information encoded in the spatial arrangement of pixel intensity and/or feature values. We propose a novel lacunarity pooling layer that aims to capture the spatial heterogeneity of the feature maps by evaluating the variability within local windows. The layer operates at multiple scales, allowin

Rajesh Jayaram, Jakub Łącki, Slobodan Mitrović, Krzysztof Onak

We consider the PageRank problem in the dynamic setting, where the goal is to explicitly maintain an approximate PageRank vector $\pi \in \mathbb{R}^n$ for a graph under a sequence of edge insertions and deletions. Our main result is a complete characterization of the complexity of dynamic PageRank maintenance for both multiplicative and additive ($L_1$) app

Yifan Zhao, Zhenyu Liang, Zhichao Lu, Ran Cheng

As one of the emerging challenges in Automated Machine Learning, the Hardware-aware Neural Architecture Search (HW-NAS) tasks can be treated as black-box multi-objective optimization problems (MOPs). An important application of HW-NAS is real-time semantic segmentation, which plays a pivotal role in autonomous driving scenarios. The HW-NAS for real-time sema

Hidetoshi Omiya, Takuya Takahashi, Takahiro Tanaka, Hirotaka Yoshino

Gravitational waves from condensates of ultra-light particles, such as axion, around rotating black holes are a promising probe to search for unknown physics. For this purpose, we need to characterize the signal to detect the gravitational waves, which requires tracking the evolution of the condensates, including various effects. The axion self-interaction c

Ming Kuo, Shouvon Sarker, Lijun Qian, Yujian Fu

In contrast to pedagogies like evidence-based teaching, personalized adaptive learning (PAL) distinguishes itself by closely monitoring the progress of individual students and tailoring the learning path to their unique knowledge and requirements. A crucial technique for effective PAL implementation is knowledge tracing, which models students' evolving knowl

Hisakazu Matsuki, Alberto Hijano, Grzegorz P. Mazur, Stefan Ilic

In 1966, Pierre-Gilles de Gennes proposed a non-volatile mechanism for switching superconductivity on and off in a magnetic device. This involved a superconductor (S) sandwiched between ferromagnetic (F) insulators in which the net magnetic exchange field could be controlled through the magnetisation-orientation of the F layers. Because superconducting switc

Shijie Zheng, Dawei Han, Heng Xu, Kejia Lee

Millisecond pulsars (MSPs) are known for their long-term stability. Using six years of observations from the Neutron Star Interior Composition Explorer (NICER), we have conducted an in-depth analysis of the X-ray timing results for six MSPs: PSRs B1937+21, B1821$-$24, J0437$-$4715, J0030+0451, J0218+4232, and J2124$-$3358. The timing stability parameter $\si

Zijie Wang, Farzana Rashid, Eduardo Blanco

People often answer yes-no questions without explicitly saying yes, no, or similar polar keywords. Figuring out the meaning of indirect answers is challenging, even for large language models. In this paper, we investigate this problem working with dialogues from multiple domains. We present new benchmarks in three diverse domains: movie scripts, tennis inter

Ricardo Chávez, Roberto Terlevich, Elena Terlevich, Ana González-Morán

Over twenty years ago, Type Ia Supernovae (SNIa) observations revealed an accelerating Universe expansion, suggesting a significant dark energy presence, often modelled as a cosmological constant, \( \Lambda \). Despite its pivotal role in cosmology, the standard $\Lambda$CDM model remains largely underexplored in the redshift range between distant SNIa and

Prabhat Agarwal, Minhazul Islam Sk, Nikil Pancha, Kurchi Subhra Hazra

In this paper, we present OmniSearchSage, a versatile and scalable system for understanding search queries, pins, and products for Pinterest search. We jointly learn a unified query embedding coupled with pin and product embeddings, leading to an improvement of $>8\%$ relevance, $>7\%$ engagement, and $>5\%$ ads CTR in Pinterest's production search system. T

Zengrui Han

We apply the better-behaved GKZ hypergeometric systems to study toric Calabi-Yau Deligne-Mumford stacks and their Hori-Vafa mirrors given by affine hypersurfaces in algebraic tori. We show that the integral structures of A-branes and B-branes coincide. This confirms a local version of a conjecture of Hosono and can be seen as a generalization of the Gamma co

Wen-Xiang Chen

This paper presents a comprehensive exploration of the thermodynamics of black holes, focusing on foundational concepts such as free energy, entropy, and topological numbers, alongside a detailed examination of quantum RN black holes. By extending the discussion to encompass the symmetry groups SO(2), SO(3)/SO(2), and SO(3) within the framework of (f(R)) gra

Hyeonseok Moon, Seungyoon Lee, Seongtae Hong, Seungjun Lee

Translating major language resources to build minor language resources becomes a widely-used approach. Particularly in translating complex data points composed of multiple components, it is common to translate each component separately. However, we argue that this practice often overlooks the interrelation between components within the same data point. To ad

Johannes Richter, Heinz-Jürgen Schmidt, Jürgen Schnack

We consider a classical Heisenberg model on the kagomé and the square kagomé lattice, where at zero magnetic field non-coplanar cuboctahedral ground states with twelve sublattices exist if suitable exchange couplings are introduced between the other neighbors. Such 'cuboc ground states' are remarkable because they allow for chiral ordering. For these

Lorenzo Cocchia, Maurizio Vergari, Tanja Kojic, Francesco Vona

One of the most promising technologies inside the Extended Reality (XR) spectrum is Augmented Reality. This technology is already in people's pockets regarding Mobile Augmented Reality with their smartphones. The scientific community still needs answers about how humans could and should interact in environments where perceived stimuli are different from

Jan-Niklas Voigt-Antons, Zhirou Sun, Maurizio Vergari, Navid Ashrafi

The auditory sense of humans is important when it comes to navigation. The importance is especially high in cases when an object of interest is visually partly or fully covered. Interactions with users of technology are mainly focused on the visual domain of navigation tasks. This paper presents the results of a literature review and user study exploring the

Takayuki Shiino, Farid Labib, Yuma Hirano, Kazuhiko Deguchi

Quasicrystal approximant (CexY1-x)Cd6 (0 < x < 1) forms a network of corner-sharing octahedra. We report that (Ce0.8Y0.2)Cd6 exhibits an anomalous magnetic transition which can be classified neither into the conventional static magnetic ordering nor into spin glasses. The anomalous transition is characterized by the coexistence of a static order and a freque

Gregor Weingart

In this article we develop a graphical calculus for stable invariants of Riemannian manifolds akin to the graphical calculus for Rozansky-Witten invariants for hyperkähler manifolds; based on interpreting trivalent graphs with colored edges as stably invariant polynomials on the space of algebraic curvature tensors. In this graphical calculus we describe exp

Igor Lugo, Martha G. Alatriste-Contreras

We analyze the concept of virtuosity as a collective attribute in music and its relationship with the entropy based on an experiment that compares two sets of digital signals played by composer-performer electric guitarists. Based on an interdisciplinary approach related to the complex systems, we computed the spectrum of signals, identified statistical dist

Sujan Maity, Dibyendu Dey, Anudeepa Ghosh, Suvadip Masanta

Induced magnetic order in a topological insulator (TI) can be realized either by depositing magnetic adatoms on the surface of a TI or engineering the interface with epitaxial thin film or stacked assembly of two-dimensional (2D) van der Waals (vdW) materials. Herein, we report the observation of spin-phonon coupling in the otherwise non-magnetic TI Bi$_\mat

Aamer Jaleel, Stephen W. Keckler, Gururaj Saileshwar

This paper focuses on mitigating DRAM Rowhammer attacks. In recent years, solutions like TRR have been deployed in DDR4 DRAM to track aggressor rows and then issue a mitigative action by refreshing neighboring victim rows. Unfortunately, such in-DRAM solutions are resource-constrained (only able to provision few tens of counters to track aggressor rows) and

Bharat Yalavarthi, Arjun Ramesh Kaushik, Arun Ross, Vishnu Boddeti

Modern face recognition systems utilize deep neural networks to extract salient features from a face. These features denote embeddings in latent space and are often stored as templates in a face recognition system. These embeddings are susceptible to data leakage and, in some cases, can even be used to reconstruct the original face image. To prevent compromi

Kai Lin, Wei-Liang Qian

In the framework of black hole perturbation theory, this work investigates the standing wave solutions in Reissner-Nordtsr\"om (RN) anti-de Sitter (AdS) spacetimes with a naked singularity. These solutions can be viewed as a specific class of quasinormal modes exhibiting distinct characteristics. The imaginary parts of their frequencies are numerically vanis

Shree Prasad Maruthi, Karrthik G. K., Vijaya Krishna A., Mahbub Hassan

The use of automotive radars is gaining popularity as a means to enhance a vehicle's sensing capabilities. However, these radars can suffer from interference caused by transmissions from other radars mounted on nearby vehicles. To address this issue, we investigate the use of an onboard intelligent reflective surface (IRS) to artificially increase a vehicle'

Riccardo Muolo, Anthony Hastir, Hiroya Nakao

The study of dynamical systems on complex networks is of paramount importance in engineering, given that many natural and artificial systems find a natural embedding on discrete topologies. For instance, power grids, chemical reactors and the brain, to name a few, can be modeled through the network formalism by considering elementary units coupled via the li

Divyansh Agarwal, Alexander R. Fabbri, Ben Risher, Philippe Laban

Prompt leakage poses a compelling security and privacy threat in LLM applications. Leakage of system prompts may compromise intellectual property, and act as adversarial reconnaissance for an attacker. A systematic evaluation of prompt leakage threats and mitigation strategies is lacking, especially for multi-turn LLM interactions. In this paper, we systemat

John Bauer, Chloe Kiddon, Eric Yeh, Alex Shan

Searching dependency graphs and manipulating them can be a time consuming and challenging task to get right. We document Semgrex, a system for searching dependency graphs, and introduce Ssurgeon, a system for manipulating the output of Semgrex. The compact language used by these systems allows for easy command line or API processing of dependencies. Addition

G. Kazakevich, R. P. Johnson, T. Khabiboulline, G. Romanov

CW magnetrons, initially developed for industrial RF heaters, were suggested to power RF cavities of superconducting accelerators due to their higher efficiency and lower cost than traditionally used klystrons, IOTs or solid-state amplifiers. RF amplifiers driven by a master oscillator serve as coherent RF sources. CW magnetrons are regenerative RF generator

Zhuoqun Li, Hongyu Lin, Tianshu Wang, Boxi Cao

Linking a claim to grounded references is a critical ability to fulfill human demands for authentic and reliable information. Current studies are limited to specific tasks like information retrieval or semantic matching, where the claim-reference relationships are unique and fixed, while the referential knowledge linking (RKL) in real-world can be much more

Isabel S. Sands, Philip F. Hopkins, Xuejian Shen, Michael Boylan-Kolchin

While galaxy rotation curves provide one of the most powerful methods for measuring dark matter profiles in the inner regions of rotation-supported galaxies, at the dwarf scale there are factors that can complicate this analysis. Given the expectation of a universal profile in dark matter-only simulations, the diversity of observed rotation curves has become

Michael V. Klibanov

The time dependent experimental data are always collected at discrete grids with respect to the time t. The step size h of such a grid is always separated from zero by a certain positive number. The same is true for all computations, which are always done on discrete grids with their grid step sizes being not too small. These applied considerations prompt us

Neha Kumari, Sumit Kumar. Sneha Priya, Ayush Kumar, Akash Fogla

In safety-critical systems that interface with the real world, the role of uncertainty in decision-making is pivotal, particularly in the context of machine learning models. For the secure functioning of Cyber-Physical Systems (CPS), it is imperative to manage such uncertainty adeptly. In this research, we focus on the development of a vehicle's lateral cont

Hang Hu, Gilles Peslherbe, Hsu Kiang Ooi, Anguang Hu

Evaluating multi-center molecular integrals with Cartesian Gaussian-type basis sets has been a long-standing bottleneck in electronic structure theory calculation for solids and molecules. We have developed a vector-coupling and vector-uncoupling scheme to solve molecular Coulomb integrals with solid harmonics basis functions(SHGO). Solid harmonics are eigen

Iason Gabriel, Arianna Manzini, Geoff Keeling, Lisa Anne Hendricks

This paper focuses on the opportunities and the ethical and societal risks posed by advanced AI assistants. We define advanced AI assistants as artificial agents with natural language interfaces, whose function is to plan and execute sequences of actions on behalf of a user, across one or more domains, in line with the user's expectations. The paper starts b

Kenny Ballou, Elena Sherman

We present \texttt{muRelBench}, a framework for synthetic benchmarks for weakly-relational abstract domains and their operations. This extensible microbenchmarking framework enables researchers to experimentally evaluate proposed algorithms for numerical abstract domains, such as closure,least-upper bound, and forget, enabling them to quickly prototype and v

Tal Ifargan, Lukas Hafner, Maor Kern, Ori Alcalay

As AI promises to accelerate scientific discovery, it remains unclear whether fully AI-driven research is possible and whether it can adhere to key scientific values, such as transparency, traceability and verifiability. Mimicking human scientific practices, we built data-to-paper, an automation platform that guides interacting LLM agents through a complete

A. Sen, C. Sumnicht, S. Adeniye, D. Patel

Communication network design for monitoring the state of an electric power grid has received significant attention in recent years. In order to measure stability of a power grid, it is imperative that measurement data collected by the Phasor Measurement Units (PMUs) located at the Sub-Stations (SS) must arrive at the Control Center (CC) within a specified de

Nolan Habel, Conor Nally, Laura Lenkic, Margaret Meixner

We present a JWST imaging survey with NIRCam and MIRI of NGC 346, the brightest star-forming region in the Small Magellanic Cloud (SMC). By combining aperture and point spread function (PSF) photometry of eleven wavelength bands across these two instruments, we have detected more than 200,000 unique sources. Using near-infrared (IR) color analysis, we observ

Zahir Alsulaimawi

This study develops a novel framework for privacy-preserving data analytics, addressing the critical challenge of balancing data utility with privacy concerns. We introduce three sophisticated algorithms: a Noise-Infusion Technique tailored for high-dimensional image data, a Variational Autoencoder (VAE) for robust feature extraction while masking sensitive

Yori Ong

In this paper, I describe a digital social communication protocol (Gridt) based on Kauffman's NK boolean networks. The main assertion is that a communication network with this topology supports infinitely scalable self-organization of collective action without requiring hierarchy or central control. The paper presents the functionality of this protocol and s

Emma A. Pappas, Rong Zhang, Cheng Peng, Robert T. Busch

Previous studies on natural samples of pampaloite (AuSbTe) revealed the crystal structure of a potentially cleavable and/or exfoliable material, while studies on natural and synthetic montbrayite (Sb-containing Au$_2$Te$_3$) claimed various chemical compositions for this low symmetry compound. Few investigations of synthetic samples have been reported for bo

Hai-Jun Zhou

Kinetically constrained spin systems are toy models of supercooled liquids and amorphous solids. In this Perspective, we revisit the prototypical Fredrickson-Andersen (FA) kinetically constrained model from the viewpoint of K-core combinatorial optimization. Each kinetic cluster of the FA system, containing all the mutually visitable microscopic occupation c

Neil Qiang Su

Functionals that explicitly depend on occupied, unoccupied, or fractionally-occupied orbitals are rigorously formalized using Clifford algebras, and a variational principle is established that facilitates orbital (and occupation) optimization as a formal implementation method. Theoretically, these methodologies circumvent the limitations encountered in the o

S. Li, S. N. Santiesteban, J. Arrington, R. Cruz-Torres

Inclusive electron scattering at carefully chosen kinematics can isolate scattering from the high-momentum nucleons in short-range correlations (SRCs). SRCs are produced by the hard, short-distance interactions of nucleons in the nucleus, and because the two-nucleon (2N) SRCs arise from the same N-N interaction in all nuclei, the cross section in the SRC-dom

Carolina Paiva, Michael Fechner, Dominik M. Juraschek

We describe a mechanism by which both ferroelectric polarization and magnetization can be created in nonpolar, nonmagnetic materials. Using a combination of phenomenological modeling and first-principles calculations, we demonstrate that ferroelectric polarization, magnetization, or both simultaneously can be transiently induced by an ultrashort laser pulse

Zhiqiang Tang, Haoyang Fang, Su Zhou, Taojiannan Yang

AutoGluon-Multimodal (AutoMM) is introduced as an open-source AutoML library designed specifically for multimodal learning. Distinguished by its exceptional ease of use, AutoMM enables fine-tuning of foundation models with just three lines of code. Supporting various modalities including image, text, and tabular data, both independently and in combination, t

Shuangyi Chen, Ashish Khisti

In the context of prediction-as-a-service, concerns about the privacy of the data and the model have been brought up and tackled via secure inference protocols. These protocols are built up by using single or multiple cryptographic tools designed under a variety of different security assumptions. In this paper, we introduce SECO, a secure inference protocol

Anupam Das, Abhishek De

We investigate the proof theory of regular expressions with fixed points, construed as a notation for (omega-)context-free grammars. Starting with a hypersequential system for regular expressions due to Das and Pous, we define its extension by least fixed points and prove soundness and completeness of its non-wellfounded proofs for the standard language mode

B. Hamil, B. C. Lütfüoğlu

We investigate the phenomenon of vacuum pair creation for Dirac fermions subjected to a Volkov plane wave and a constant electric field within the framework of spin noncommutativity of coordinates. Employing the Schwinger proper-time formalism, we derive the effective action and obtain closed-form expressions for the pair creation probability. Our analysis r

Hassan Allami, Daniel Miravet, Marek Korkusinski, Pawel Hawrylak

We present a theory of a two qubit gate with macroscopic singlet-triplet (ST) qubits in synthetic spin-one chains in InAsP quantum dot nanowires. The macroscopic topologically protected singlet-triplet qubits are built with two spin-half Haldane quasiparticles. The Haldane quasiparticles are hosted by synthetic spin-one chain realized in chains of InAsP quan

Ryan Martin

The false confidence theorem establishes that, for any data-driven, precise-probabilistic method for uncertainty quantification, there exists (non-trivial) false hypotheses to which the method tends to assign high confidence. This raises concerns about the reliability of these widely-used methods, and shines new light on the consonant belief function-based m

Pengju Chen, Da-Wei Luo, Ting Yu

We investigated the optimal control of a continuous variable system, focusing on entanglement generation in an optomechanical system without utilizing Fock basis cutoffs. Using the Krotov algorithm to optimize the dynamics of the covariance matrix, we illustrated how to design a control objective function to manipulate the dynamics of the system to generate

Diogo A. P. Nunes, Joana Ferreira-Gomes, Fani Neto, David Martins de Matos

Objectives: This study aims to systematically review the literature on the computational processing of the language of pain, or pain narratives, whether generated by patients or physicians, identifying current trends and challenges. Methods: Following the PRISMA guidelines, a comprehensive literature search was conducted to select relevant studies on the com

Glen D. Gillen

A series of tutorials, assessments, and instructor guides are presented as a complete package for an upper-level undergraduate, or lower-level graduate, laboratory-based course, or extended new-student seminar. The purpose of this package is to teach the students essential skills beneficial for working in an experimental optical laboratory by introducing the

Ahmet Kara, Zheng Luo, Milos Nikolic, Dan Olteanu

We investigate the evaluation of conjunctive queries over static and dynamic relations. While static relations are given as input and do not change, dynamic relations are subject to inserts and deletes. We characterise syntactically three classes of queries that admit constant update time and constant enumeration delay. We call such queries tractable. Depend

Marcos V. Conde, Florin-Alexandru Vasluianu, Radu Timofte, Jianxing Zhang

This paper reviews the NTIRE 2024 RAW Image Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Super-Resolution could be essential in modern Image Signal Processing (ISP) pipelines, however, this problem is not as explored as in the RGB domain. Th goal of this challenge is to upscale RAW Bayer images by 2x, consi

Tushar Nagarajan, Lorenzo Torresani

Comparing a user video to a reference how-to video is a key requirement for AR/VR technology delivering personalized assistance tailored to the user's progress. However, current approaches for language-based assistance can only answer questions about a single video. We propose an approach that first automatically generates large amounts of visual instruction

Davit Melikidze, Alexander Gamkrelidze

This research proposes a novel approach to the Word Sense Disambiguation (WSD) task in the Georgian language, based on supervised fine-tuning of a pre-trained Large Language Model (LLM) on a dataset formed by filtering the Georgian Common Crawls corpus. The dataset is used to train a classifier for words with multiple senses. Additionally, we present experim

Ruilong Li, Sanja Fidler, Angjoo Kanazawa, Francis Williams

We present NeRF-XL, a principled method for distributing Neural Radiance Fields (NeRFs) across multiple GPUs, thus enabling the training and rendering of NeRFs with an arbitrarily large capacity. We begin by revisiting existing multi-GPU approaches, which decompose large scenes into multiple independently trained NeRFs, and identify several fundamental issue

Sadmir Kudin, Enes Pasalic, Alexandr Polujan, Fengrong Zhang

Every Boolean bent function $f$ can be written either as a concatenation $f=f_1||f_2$ of two complementary semi-bent functions $f_1,f_2$; or as a concatenation $f=f_1||f_2||f_3||f_4$ of four Boolean functions $f_1,f_2,f_3,f_4$, all of which are simultaneously bent, semi-bent, or 5-valued spectra-functions. In this context, it is essential to ask: When does a

Ziyue Qiu, Juncheng Yang, Mor Harchol-Balter

Software caches are an intrinsic component of almost every computer system. Consequently, caching algorithms, particularly eviction policies, are the topic of many papers. Almost all these prior papers evaluate the caching algorithm based on its hit ratio, namely the fraction of requests that are found in the cache, as opposed to disk. The hit ratio is viewe

Simon Neumeyer, Julian Stier, Michael Granitzer

Neural architecture search (NAS) is a challenging problem. Hierarchical search spaces allow for cheap evaluations of neural network sub modules to serve as surrogate for architecture evaluations. Yet, sometimes the hierarchy is too restrictive or the surrogate fails to generalize. We present FaDE which uses differentiable architecture search to obtain relati

Shivam Bansal, Keerti Choudhary, Harkirat Dhanoa, Harsh Wardhan

Given a directed graph $G = (V, E)$ with $n$ vertices, $m$ edges and a designated source vertex $s\in V$, we consider the question of finding a sparse subgraph $H$ of $G$ that preserves the flow from $s$ up to a given threshold $\lambda$ even after failure of $k$ edges. We refer to such subgraphs as $(\lambda,k)$-fault-tolerant bounded-flow-preserver ($(\lam

Arjun Somayazulu, Sagnik Majumder, Changan Chen, Kristen Grauman

An environment acoustic model represents how sound is transformed by the physical characteristics of an indoor environment, for any given source/receiver location. Traditional methods for constructing acoustic models involve expensive and time-consuming collection of large quantities of acoustic data at dense spatial locations in the space, or rely on privil

Hunter Waldron

Andrews and Keith recently produced a general Schmidt type partition theorem using a novel interpretation of Stockhofe's bijection, which they used to find new $q$-series identities. This includes an identity for a trivariate 2-colored partition generating function. In this paper, their Schmidt type theorem is further generalized akin to how Franklin classic

Lorenzo Gotta, Thierry Giamarchi

We consider a linearly-dispersing quantum impurity interacting through a contact density-density term with a one-dimensional (1D) superfluid described by the Tomonaga-Luttinger liquid theory. Using a linked cluster expansion we characterize the impurity dynamics by calculating approximate expressions for the single-particle Green's function and for the time

Matthew Alan Le Brun, Ornela Dardha

MAG$\pi$ is a Multiparty, Asynchronous and Generalised $\pi$-calculus that introduces timeouts into session types as a means of reasoning about failure-prone communication. Its type system guarantees that all possible message-loss is handled by timeout branches. In this work, we argue that the previous is unnecessarily strict. We present MAG$\pi$!, an extens

Sifat Muhammad Abdullah, Aravind Cheruvu, Shravya Kanchi, Taejoong Chung

Deepfake or synthetic images produced using deep generative models pose serious risks to online platforms. This has triggered several research efforts to accurately detect deepfake images, achieving excellent performance on publicly available deepfake datasets. In this work, we study 8 state-of-the-art detectors and argue that they are far from being ready f

Vero Estrada-Galiñanes, Ahmad ElRouby, Léo Marc-André Theytaz

Inefficient data management has been the Achilles heel of blockchain-based decentralized applications (dApps). An off-chain storage layer, which lies between the application and the blockchain layers, can improve space efficiency and data availability with erasure codes and decentralized maintenance. This paper presents two fundamental components of such sto

A. Stewart Fotheringham, Chen-Lun Kao, Hanchen Yu, Sarah Bardin

Local spatial models such as Geographically Weighted Regression (GWR) and Multiscale Geographically Weighted Regression (MGWR) serve as instrumental tools to capture intrinsic contextual effects through the estimates of the local intercepts and behavioral contextual effects through estimates of the local slope parameters. GWR and MGWR provide simple implemen

Sahil Hassan, Michael Inouye, Miguel C. Gonzalez, Ilkin Aliyev

Open-source simulation tools play a crucial role for neuromorphic application engineers and hardware architects to investigate performance bottlenecks and explore design optimizations before committing to silicon. Reconfigurable Architecture for Neuromorphic Computing (RANC) is one such tool that offers ability to execute pre-trained Spiking Neural Network (

Akanksha Bhardwaj, Partha Konar, Vishal S. Ngairangbam

Deep learning algorithms will play a key role in the upcoming runs of the Large Hadron Collider (LHC), helping bolster various fronts ranging from fast and accurate detector simulations to physics analysis probing possible deviations from the Standard Model. The game-changing feature of these new algorithms is the ability to extract relevant information from

Charlie Nation, Hallmann Oskar Gestsson, Alexandra Olaya-Castro

We theoretically investigate polarization-filtered two-photon correlations for the light emitted by a multichromophoric system undergoing excitation transport under realistic exciton-phonon interactions, and subject to continuous incoherent illumination. We show that for a biomolecular aggregate, such as the Fenna-Matthews Olson (FMO) photosynthetic complex,

Sakher Khalil Alqaaidi, Krzysztof Kochut

Knowledge Graphs (KGs) are widely employed in artificial intelligence applications, such as question-answering and recommendation systems. However, KGs are frequently found to be incomplete. While much of the existing literature focuses on predicting missing nodes for given incomplete KG triples, there remains an opportunity to complete KGs by exploring rela

Marcos V. Conde, Saman Zadtootaghaj, Nabajeet Barman, Radu Timofte

This paper reviews the AIS 2024 Video Quality Assessment (VQA) Challenge, focused on User-Generated Content (UGC). The aim of this challenge is to gather deep learning-based methods capable of estimating the perceptual quality of UGC videos. The user-generated videos from the YouTube UGC Dataset include diverse content (sports, games, lyrics, anime, etc.), q

Si-Yi Chen, Jessica Illiano, Angela Sara Cacciapuoti, Marcello Caleffi

Entanglement is unanimously recognized as the key communication resource of the Quantum Internet. Yet, the possibility of implementing novel network functionalities by exploiting the marvels of entanglement has been poorly investigated so far, by mainly restricting the attention to bipartite entanglement. Conversely, in this paper, we aim at exploiting multi

Guangpeng Xu, Jeffrey Carvalho, Chiran Wijesundara, Tim Thomay

The classification of higher-order photon emission becomes important with more methods being developed for deterministic multiphoton generation. The widely-used second-order correlation g(2) is not sufficient to determine the quantum purity of higher photon Fock states. Traditional characterization methods require a large amount of photon detection events wh